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Renn F
de82e06b3c
Recall no longer depends on a per-query HyDE LLM call — it comes from the index. Each chunks_<type> table gets a generated `tsv` column + GIN index (migration 031; the engine CREATE TABLE matches so fresh tables get it too). VectorStore.hybrid_search fuses pgvector cosine with Postgres full-text in one query: score = min(1, cosine + 0.3 * normalized_ts_rank). A vector-only match keeps its cosine score (so decisions/reviewer thresholds are unchanged), a keyword match adds a bounded boost (the recall win), and a keyword-only match stays low. Empty/garbage query text degrades to pure vector. HyDE is removed from the search hot path: _compute_query_embedding now embeds the query directly, and _generate_hyde_passage / rag_use_hyde / IndexConfig.use_hyde are deleted. So a search is one local embed + one indexed SQL — no LLM round-trip. The raw query text is threaded through the embed-once + concurrent fan-out (search_with_embedding(embedding, query_text)). Verified live via a real pgvector round-trip: vector ranking + keyword boost + [0,1] scores + empty-query fallback all correct. Adds wiring + fan-out unit tests; the fusion SQL itself is verified live (needs pgvector, not gated in CI).